Alpagasus: Training a better alpaca with fewer data L Chen, S Li, J Yan, H Wang, K Gunaratna, V Yadav, Z Tang, V Srinivasan, ... arXiv preprint arXiv:2307.08701, 2023 | 175 | 2023 |
Backdooring instruction-tuned large language models with virtual prompt injection J Yan, V Yadav, S Li, L Chen, Z Tang, H Wang, V Srinivasan, X Ren, H Jin Proceedings of the 2024 Conference of the North American Chapter of the …, 2024 | 72* | 2024 |
Eidos, INDRA, & Delphi: from free text to executable causal models R Sharp, A Pyarelal, B Gyori, K Alcock, E Laparra, ... Proceedings of the 2019 conference of the north American chapter of the …, 2019 | 30 | 2019 |
Instruction-following evaluation through verbalizer manipulation S Li, J Yan, H Wang, Z Tang, X Ren, V Srinivasan, H Jin arXiv preprint arXiv:2307.10558, 2023 | 20 | 2023 |
How may i help you? using neural text simplification to improve downstream nlp tasks H Van, Z Tang, M Surdeanu arXiv preprint arXiv:2109.04604, 2021 | 20 | 2021 |
Exploring interpretability in event extraction: Multitask learning of a neural event classifier and an explanation decoder Z Tang, G Hahn-Powell, M Surdeanu Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 14 | 2020 |
It takes two flints to make a fire: Multitask learning of neural relation and explanation classifiers Z Tang, M Surdeanu Computational Linguistics 49 (1), 117-156, 2023 | 8 | 2023 |
Interpretability rules: Jointly bootstrapping a neural relation extractorwith an explanation decoder Z Tang, M Surdeanu Proceedings of the first workshop on trustworthy natural language processing …, 2021 | 4 | 2021 |
Pag-llm: Paraphrase and aggregate with large language models for minimizing intent classification errors V Yadav, Z Tang, V Srinivasan Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024 | 3 | 2024 |
Bootstrapping neural relation and explanation classifiers Z Tang, M Surdeanu Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 2 | 2023 |
DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models S Gao, CH Lin, T Hua, T Zheng, Y Shen, H Jin, YC Hsu arXiv preprint arXiv:2410.11988, 2024 | | 2024 |
Interpretable Natural Language Processing with Applications to Information Extraction Z Tang The University of Arizona, 2022 | | 2022 |
Taxonomy Builder: a Data-driven and User-centric Tool for Streamlining Taxonomy Construction J Hungerford, YS Chan, J MacBride, BM Gyori, A Zupon, Z Tang, ... Association for Computational Linguistics (ACL), 2022 | | 2022 |
Alert Generation in Execution Monitoring Using Resource Envelopes TKS Kumar, H Xu, Z Tang, A Kumar, CM Rogers, CA Knoblock The Thirty-First International Flairs Conference, 2018 | | 2018 |
A Distributed Logical Filter for Connected Row Convex Constraints TKS Kumar, H Xu, Z Tang, A Kumar, CM Rogers, CA Knoblock 2017 IEEE 29th International Conference on Tools with Artificial …, 2017 | | 2017 |